View source: R/get_adjacencies.R
get_adjacencies | R Documentation |
Fast calculation of adjacencies between classes in a raster
get_adjacencies(landscape, neighbourhood = 4, what = "full", upper = FALSE)
landscape |
A categorical raster object: SpatRaster; Raster* Layer, Stack, Brick; stars or a list of SpatRasters. |
neighbourhood |
The number of directions in which cell adjacencies are considered as neighbours: 4 (rook's case), 8 (queen's case) or a binary matrix where the ones define the neighbourhood. The default is 4. |
what |
Which adjacencies to calculate: "full" for a full adjacency matrix, "like" for the diagonal, "unlike" for the off diagonal part of the matrix and "triangle" for a triangular matrix counting adjacencies only once. |
upper |
Logical value indicating whether the upper triangle of the adjacency matrix should be returned (default FALSE). |
A fast implementation with Rcpp to calculate the adjacency matrix for raster. The adjacency matrix is most often used in landscape metrics to describe the configuration of landscapes, is it is a cellwise count of edges between classes.
The "full" adjacency matrix is double-count method, as it contains the pairwise counts of cells between all classes. The diagonal of this matrix contains the like adjacencies, a count for how many edges a shared in each class with the same class.
The "unlike" adjacencies are counting the cellwise edges between different classes.
matrix with adjacencies between classes in a raster and between cells from the same class.
landscape <- terra::rast(landscapemetrics::landscape)
# calculate full adjacency matrix
get_adjacencies(landscape, 4)
# equivalent with the terra package:
adjacencies <- terra::adjacent(landscape, 1:terra::ncell(landscape), "rook", pairs = TRUE)
table(terra::values(landscape, mat = FALSE)[adjacencies[,1]],
terra::values(landscape, mat = FALSE)[adjacencies[,2]])
# count diagonal neighbour adjacencies
diagonal_matrix <- matrix(c(1, NA, 1,
NA, 0, NA,
1, NA, 1), 3, 3, byrow = TRUE)
get_adjacencies(landscape, diagonal_matrix)
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